• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.553-562
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• 2017

GPS (Global Positioning System) receiver among various sensors mounted on UAV (Unmanned Aerial Vehicle) helps to perform various functions such as hovering flight and waypoint flight based on GPS signals. GPS receiver can be used in an environment where GPS signals are smoothly received. However, recently, the use of UAV has been diversifying into various fields such as facility monitoring, delivery service and leisure as UAV's application field has been expended. For this reason, GPS signals may be interrupted by UAV's flight in a shadow area where the GPS signal is limited. Multipath can also include various noises in the signal, while flying in dense areas such as high-rise buildings. In this study, we used analytical photogrammetry and auto tracking total station technique for 3D positioning of UAV. The analytical photogrammetry is based on the bundle adjustment using the collinearity equations, which is the geometric principle of the center projection. The auto tracking total station technique is based on the principle of tracking the 360 degree prism target in units of seconds or less. In both techniques, the target used for positioning the UAV is mounted on top of the UAV and there is a geometric separation in the x, y and z directions between the targets. Data were acquired at different speeds of 0.86m/s, 1.5m/s and 2.4m/s to verify the flight speed of the UAV. Accuracy was evaluated by geometric separation of the target. As a result, there was an error from 1mm to 12.9cm in the x and y directions of the UAV flight. In the z direction with relatively small movement, approximately 7cm error occurred regardless of the flight speed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.545-554
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• 2019

This research aims to provide a building area extraction approach over the areas where data acquisition is impossible through field surveying, aerial photography and lidar scanning. Hence, high-resolution satellite images, which have high accessibility over the earth, are utilized for the automated building extraction in this study. 3D point clouds or DSM (Digital Surface Models), derived from the stereo image matching process, provides low quality of building area extraction due to their high level of noises and holes. In this regards, this research proposes a hybrid building area extraction approach which utilizes 3D point clouds (from image matching), and color and linear information (from imagery). First of all, ground and non-ground points are separated from 3D point clouds; then, the initial building hypothesis is extracted from the non-ground points. Secondly, color based building hypothesis is produced by considering the overlapping between the initial building hypothesis and the color segmentation result. Afterwards, line detection and space partitioning results are utilized to acquire the final building areas. The proposed approach shows 98.44% of correctness, 95.05% of completeness, and 1.05m of positional accuracy. Moreover, we see the possibility that the irregular shapes of building areas can be extracted through the proposed approach.

• Economic and Environmental Geology
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• v.40 no.4
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• pp.445-459
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• 2007

Superconducting Gravimeter(SG) was installed and has been successfully operated at MunGyung, Kyungsang province in Korea in March 2005. It was registered as the 21st observatory of the Global Geodynamics Project. Since SG can precisely measure the gravity variations below the 1mHz frequency band, it has the outstanding capability to sense and resolve many different periodic gravity components from each other. From the raw data collected between 18 March 2005 and 21 February 2006 diurnal and semi-diurnal tidal band's residual gravity components were analyzed. During this process, the instrumental noises, air pressure, and ground water corrections were carried out. Values of $-3.18nm/s^2/hPa\;and\;17nm/s^2/m$ were used respectively in the air pressure and groundwater corrections. Hartmann-Wenzel and Whar-Dehant Earth tide models were adopted to compute the residual gravity for Q1, O1, P1, K1, M2, N2, S2, K2 tidal bands. For the ocean loading correction, SCW80, FES952, and FES02 models were used and compared. As a result, FES02 ocean loading model has shown the best match for the data processing at MunGyung SG MunGyung SG gravity was compared with GRACE satellite gravity. The correlation coefficient between the two gravity after groundwater correction was 0.628, which is higher than before ground water correction. To evaluate sensitivity at MunGyung SG gravity statition, the gravity data measured during 2005 Indodesian earthquake was compared with STS-2 broad band seismometer data. The result clearly revealed that the SG could recorded the same period of earthquake with seismometer event and a few after-shock events those were detected by seismometer.

• Journal of Korea Water Resources Association
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• v.51 no.1
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• pp.19-33
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• 2018

This study proposed a rainfall-runoff model for the purpose of real-time flood warning in urban basins. The proposed model was based on the shot noise process, which is expressed as a sum of shot noises determined independently with the peak value, decay parameter and time delay of each sub-basin. The proposed model was different from other rainfall-runoff models from the point that the runoff from each sub-basin reaches the basin outlet independently. The model parameters can be easily determined by the empirical formulas for the concentration time and storage coefficient of a basin and those of the pipe flow. The proposed model was applied to the total of three rainfall events observed at the Jungdong, Guro 1 and Daerim 2 pumping stations to evaluate its applicability. Summarizing the results is as follows. (1) The unit response function of the proposed model, different from other rainfall-runoff models, has the same shape regardless of the rainfall duration. (2) The proposed model shows a convergent shape as the calculation time interval becomes smaller. As the proposed model was proposed to be applied to urban basins, one-minute of calculation time interval would be most appropriate. (3) Application of the one-minute unit response function to the observed rainfall events showed that the simulated runoff hydrographs were very similar to those observed. This result indicates that the proposed model has a good application potential for the rainfall-runoff analysis in urban basins.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1244-1244
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from mastitic and healthy cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from mastitic and healthy cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA and FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference, thereby providing a useful means for spectroscopy-based clinic applications.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.1211-1214
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• 1992

AC servo motor drives, Fara DS series, proposed in this paper can be effectively used in robots, CNC machine tools, and FA system with AC servo motors as actuators. The inverter of the AC servo drive consists of IGBT (Insulated Gate Bipolar Transistor) which have high switching frequency. Noises and vibrations generated in variable speed control of AC servo motors can be greatly reduced due to their high switching frequencies. In the developed servo drive, maximum torque is always generated in the whole speed range by compensating phase shift, which results from the nonlinearies of the AC servo motor during abrupt acceleration and deceleration. Abundant protection functions are provided to prevent abnormal state of the servo motor, and furthermore diverse user options are considered provided for the effective application. The proposed AC servo motor drive is designed to minimize velocity variation with respect to external load, supply voltage, environmental temperature, and humidity, so can be widely used in the fields of factory automation including robots and CNC msachine tools.

• The Journal of the Acoustical Society of Korea
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• v.15 no.5
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• pp.38-43
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• 1996

This paper compares the recognition performances of feature vectors known to be robust to the environmental noise. And, the speech subtraction technique is combined with the noise robust feature to get more performance enhancement. The experiments using SMC(Short time Modified Coherence) analysis, root cepstral analysis, LDA(Linear Discriminant Analysis), PLP(Perceptual Linear Prediction), RASTA(RelAtive SpecTrAl) processing are carried out. An isolated word recognition system is composed using semi-continuous HMM. Noisy environment experiments usign two types of noises:exhibition hall, computer room are carried out at 0, 10, 20dB SNRs. The experimental result shows that SMC and root based mel cepstrum(root_mel cepstrum) show 9.86% and 12.68% recognition enhancement at 10dB in compare to the LPCC(Linear Prediction Cepstral Coefficient). And when combined with spectral subtraction, mel cepstrum and root_mel cepstrum show 16.7% and 8.4% enhanced recognition rate of 94.91% and 94.28% at 10dB.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.6
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• pp.751-758
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• 2015

Noise prediction for HVAC(Heating, Ventilating and Air Conditioning) systems are normally performed by empirical method suggested by NEBB(National Environmental Balancing Bureau, 1994). However, the method is not suitable for large ducts in ships. In this paper, computational analysis methods are used to develop a noise prediction method for the large ducts in ships. To develop regression formula of attenuation of sound pressure level in large ducts, Boundary Element Method(BEM) is used. BEM and Computational Fluid Dynamics(CFD) are applied to the analysis of flow-induced noise in ducts with stiffeners inside. Loud noise above 100 dB can be generated in some cases. Breakout noises of large ducts are also analyzed by using BEM and Finite Element Method(FEM). The acoustic pressure level shows about 10-15dB difference between inside and outside of the duct. Utilizing the results of this study, it is expected that shipyard planners can predict noise of the HVAC system for ships.

• Journal of the Korean Geophysical Society
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• v.5 no.1
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• pp.9-18
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• 2002

We performed a long-term monitoring of self-potential(SP) using the Cu-CuSO₄non-polarizable electrode and copper-clad electrodes(CCE) in a test site in order to analyze the effects of surrounding environmental noises such as temperature, rainfall and soil moisture content on the electrodes. Analysis of the temperature dependence of the non-polarizable electrodes showed that is temperature coefficient was about +0.5 mV/°Fwhen its end was exposed to atmosphere while it was less than +0.5 mV/℃ when submerged into the subsurface, which reflects that there exists an 8 to 11 hour lag between temperatures at the depth of 15 cm and atmosphere. CCE was independent of atmospheric temperature in subsurface but showed temperature coefficient of 1.0 mV/℃ when exposed to atmosphere. Drifts of 1 to 2 mV recorded with the non-polarizable electrode directly related to the soil moisture content when it was buried in subsurface. Drift with CCE also showed similar trend to the soil moisture content, and 5 mV drift was recorded according to 5% of daily variation. The soil moisture content had strong effects on the measurement with CCE in rainfall since the flow potential is generated on the surface of the electrode.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1709-1718
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• 2021

The waveform data of the Airborne Bathymetric LiDAR (ABL; LiDAR: Light Detection And Ranging) system provides data with improved accuracy, resolution, and reliability compared to the discrete-return data, and increases the user's control over data processing. Furthermore, we are able to extract additional information about the return signal. Waveform decomposition is a technique that separates each echo from the received waveform with a mixture of water surface and seabed reflections, waterbody backscattering, and various noises. In this study, a new waveform decomposition technique based on a Gaussian model was developed to improve the point extraction performance from the ABL waveform data. In the existing waveform decomposition techniques, the number of decomposed echoes and decomposition performance depend on the peak detection results because they use waveform peaks as initial values. However, in the study, we improved the approximation accuracy of the decomposition model by adding the estimated potential peak candidates to the initial peaks. As a result of an experiment using waveform data obtained from the East Coast from the Seahawk system, the precision of the decomposition model was improved by about 37% based on evaluating RMSE compared to the Gaussian decomposition method.